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Assessing chronic obstructive pulmonary disease risk based on exhalation and cough sounds.
Biomedical engineering online
Jul 5, 2025
BACKGROUND AND OBJECTIVE: Chronic obstructive pulmonary disease (COPD), a progressively worsening respiratory condition, severely impacts patient quality of life. Early risk assessment can improve treatment outcomes and lessen healthcare burdens. How...
Serum tryptophan-kynurenine metabolites served as biomarkers of disease activity in rheumatoid arthritis and linked to immune imbalance.
Arthritis research & therapy
Jul 5, 2025
BACKGROUND: Immune imbalance caused by imbalanced helper T(Th)17/regulatory T (Treg) and follicular helper T (Tfh)/follicular regulatory T (Tfr) cells drives the onset of rheumatoid arthritis (RA) fundamentally. Tryptophan (Trp) metabolism is crucial...
Predictive modeling and machine learning show poor performance of clinical, morphological, and hemodynamic parameters for small intracranial aneurysm rupture.
Scientific reports
Jul 5, 2025
Small intracranial aneurysms (SIAs) (< 5 mm) are increasingly detected due to advanced imaging, but predicting rupture risk remains challenging. Rupture, though rare, can cause devastating subarachnoid hemorrhage. This study analyzed 141 SIAs (101 un...
Early warning and stratification of the elderly cardiopulmonary dysfunction-related diseases: multicentre prospective study protocol.
BMJ open
Jul 5, 2025
INTRODUCTION: In China, there is a lack of standardised clinical imaging databases for multidimensional evaluation of cardiopulmonary diseases. To address this gap, this study protocol launched a project to build a clinical imaging technology integra...
Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China.
BMJ open
Jul 5, 2025
OBJECTIVE: To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced decision-making and targeted health management in integrat...
Leveraging heterogeneous tabular of EHRs with prompt learning for clinical prediction.
Journal of biomedical informatics
Jul 4, 2025
Electronic Health Records (EHRs) depict patient-related information and have significantly contributed to advancements in healthcare fields. The abundance of EHR data provides exceptional opportunities for developing clinical predictive models. Howev...
Machine-learning based strategy identifies a robust protein biomarker panel for Alzheimer's disease in cerebrospinal fluid.
Alzheimer's research & therapy
Jul 4, 2025
BACKGROUND: The complex pathogenesis of Alzheimer's disease (AD) has resulted in limited current biomarkers for its classification and diagnosis, necessitating further investigation into reliable universal biomarkers or combinations.
Machine learning-based predictive tools and nomogram for in-hospital mortality in critically ill cancer patients: development and external validation using retrospective cohorts.
BMC medical informatics and decision making
Jul 4, 2025
BACKGROUND: The incidence of intensive care unit (ICU) admissions and the corresponding mortality rates among cancer patients are both high. However, the existing scoring systems all lack specificity. This research seeks to establish and validate a p...
Predicting ESWL success for ureteral stones: a radiomics-based machine learning approach.
BMC medical imaging
Jul 4, 2025
OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model that integrates radiomics and conventional radiological features to predict the success of single-session extracorporeal shock wave lithotripsy (ESWL) for ureteral sto...
Deep learning-based classification of parotid gland tumors: integrating dynamic contrast-enhanced MRI for enhanced diagnostic accuracy.
BMC medical imaging
Jul 4, 2025
BACKGROUND: To evaluate the performance of deep learning models in classifying parotid gland tumors using T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted MR images, along with DCE data derived from time-intensity curves.
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